Changes for page SGA3 D1.5 Showcase 1

Last modified by gorkazl on 2023/11/13 14:27
From version 17.1
edited by fousekjan
on 2023/10/31 09:44
Change comment: There is no comment for this version
To version 13.2
edited by gorkazl
on 2023/10/09 17:46
Change comment: There is no comment for this version

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1 -XWiki.fousekjan
1 +XWiki.gorkazl
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24 24  (((
25 25  Running the notebooks //**requires an EBRANS account**// with permissions to access the Lab and programmatic access to the Knowledge Graph API. In addition, to interact with the HPC infrastructure, the user needs access to an active allocation on the corresponding FENIX site. Lastly, the virtual ageing brain notebooks write data to the Bucket storage.
26 26  
27 -Please, to be able to interact with the material fully, //**make first a private working duplicate**// of this Collab using the notebook [[copy_showcase1_collab.ipynb>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/SGA3%20D1.5%20Showcase%201/copy_showcase1_collab.ipynb]]. If you encounter any issues running the notebooks, contact [[The Virtual Brain Facility Hub>>mailto:jan.fousek@univ-amu.fr]].
27 +Please, to avoid overwriting precomputed data, //**make first a private working duplicate**// of this Collab using the notebook [[copy_showcase1_collab.ipynb>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/SGA3%20D1.2%20Showcase%201/copy_showcase1_collab.ipynb]]. If you encounter any issues running the notebooks, contact [[The Virtual Brain Facility Hub>>mailto:jan.fousek@univ-amu.fr]].
28 28  )))
29 29  )))
30 30  
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36 36  (% class="wikigeneratedid" %)
37 37  See the details of the first study in the following publication:
38 38  
39 -Lavanga, M., Stumme, J., Yalcinkaya, B. H., Fousek, J., Jockwitz, C., Sheheitli, H., Bittner, N., Hashemi, M., Petkoski, S., Caspers, S., & Jirsa, V. (2023)[[. The virtual aging brain: Causal inference supports interhemispheric dedifferentiation in healthy aging.>>https://doi.org/10.1016/j.neuroimage.2023.120403]] //NeuroImage//, //283//, 120403.
39 +M. Lavanga, J. Stumme, B. H. Yalcinkaya, J. Fousek, C. Jockwitz, H. Sheheitli, N. Bittner, M. Hashemi, S. Petkoski, S. Caspers, and V. Jirsa, [[The Virtual Aging Brain: A Model-Driven Explanation for Cognitive Decline in Older Subjects>>https://doi.org/10.1101/2022.02.17.480902]].
40 40  
41 41  === Simulation of resting-state activity ===
42 42  
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49 49  
50 50  Link to the notebook:
51 51  
52 -* [[virtual_ageing/notebooks/1_BNM_for_resting_state.ipynb>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/SGA3%20D1.5%20Showcase%201/virtual_ageing/notebooks/1_BNM_for_resting_state.ipynb]]
52 +* [[virtual_ageing/notebooks/1_BNM_for_resting_state.ipynb>>https://lab.ch.ebrains.eu/user-redirect/lab/tree/shared/SGA3%20D1.2%20Showcase%201/virtual_ageing/notebooks/1_BNM_for_resting_state.ipynb]]
53 53  
54 -[[image:https://wiki.ebrains.eu/bin/download/Collabs/sga3-d1-2-showcase-1/WebHome/image-20220103100841-2.png?rev=1.1||alt="image-20220103100841-2.png"]]
54 +[[image:image-20220103100841-2.png]]
55 55  
56 56  === Virtual ageing trajectories ===
57 57  
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63 63  
64 64  Link to the notebook:
65 65  
66 -* [[virtual_ageing/notebooks/2_virtual_ageing_trajectories.ipynb>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/SGA3%20D1.5%20Showcase%201/virtual_ageing/notebooks/2_virtual_ageing_trajectories.ipynb]]
66 +* [[virtual_ageing/notebooks/2_virtual_ageing_trajectories.ipynb>>https://lab.ch.ebrains.eu/user-redirect/lab/tree/shared/SGA3%20D1.2%20Showcase%201/virtual_ageing/notebooks/2_virtual_ageing_trajectories.ipynb]]
67 67  
68 -[[image:https://wiki.ebrains.eu/bin/download/Collabs/sga3-d1-2-showcase-1/WebHome/image-20220103101022-3.png?rev=1.1||alt="image-20220103101022-3.png"]]
68 +[[image:image-20220103101022-3.png]]
69 69  
70 70  === Inference with SBI ===
71 71  
72 72  The last step of the inter-individual variability workflow employs Simulation Based Inference for estimation of the full posterior values of the parameters. Here, a deep neural estimator is trained to provide a relationship between the parameters of a model (black box simulator) and selected descriptive statistics of the observed data.
73 73  
74 -[[image:https://wiki.ebrains.eu/bin/download/Collabs/sga3-d1-2-showcase-1/WebHome/image-20220103104332-4.png?width=418&height=418&rev=1.1||alt="image-20220103104332-4.png"]]
74 +[[image:image-20220103104332-4.png||height="418" width="418"]]
75 75  
76 76  Link to the notebook:
77 77  
78 -* [[virtual_ageing/notebooks/3_inference_with_SBI.ipynb>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/SGA3%20D1.5%20Showcase%201/virtual_ageing/notebooks/3_inference_with_SBI.ipynb]]
78 +* [[virtual_ageing/notebooks/3_inference_with_SBI.ipynb>>https://lab.ch.ebrains.eu/user-redirect/lab/tree/shared/SGA3%20D1.2%20Showcase%201/virtual_ageing/notebooks/3_inference_with_SBI.ipynb]]
79 79  
80 80  == b. Regional variability – Receptor density maps ==
81 81  
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91 91  
92 92  The three datasets are characterised in the same parcellation. Link to the notebook:
93 93  
94 -* [[regional_variability/notebooks/1_load_data.ipynb>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/SGA3%20D1.5%20Showcase%201/regional_variability/notebooks/1_load_data.ipynb]]
94 +* [[regional_variability/notebooks/1_load_data.ipynb>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/SGA3%20D1.2%20Showcase%201/regional_variability/notebooks/1_load_data.ipynb]]
95 95  
96 -[[image:https://wiki.ebrains.eu/bin/download/Collabs/sga3-d1-2-showcase-1/WebHome/download%20-%202022-02-10T130815.902.png?rev=1.1||alt="region-wise gene expression heterogeneity"]]
96 +(% style="text-align:center" %)
97 +[[image:download - 2022-02-10T130815.902.png||alt="region-wise gene expression heterogeneity"]]
97 97  
98 98  === Fitting model parameters with regional bias ===
99 99  
100 -A series of simulations of the whole-brain network model are launched in the EBRAINS HPC facilities in order to identify the optimal model parameters leading to simulated resting-state brain activity that best resembles the empirically observed activity. In this branch of the showcase, brain regions are simulated using the mean-field AdEx population model; specifically modified to account for the regional densities of GABAa and AMPA neuroreceptors. See the details in the following document.
101 +A series of simulations of the whole-brain network model are launched in the EBRAINS HPC facilities in order to identify the optimal model parameters leading to simulated resting-state brain activity that best resembles the empirically observed activity. In this branch of the showcase, brain regions are simulated using the mean-field AdEx population model; specifically modified to account for the regional densities of GABAa and AMPA neuroreceptors. See the details following document.
101 101  
102 102  Link to the notebook:
103 103  
104 -* [[regional_variability/notebooks/2_parameter_swep.ipynb>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/SGA3%20D1.5%20Showcase%201/regional_variability/notebooks/2_parameter_swep.ipynb]]
105 +* [[regional_variability/notebooks/2_parameter_swep.ipynb>>https://lab.ch.ebrains.eu/hub/user-redirect/lab/tree/shared/SGA3%20D1.2%20Showcase%201/regional_variability/notebooks/2_parameter_swep.ipynb]]
105 105  
106 -[[image:https://wiki.ebrains.eu/bin/download/Collabs/sga3-d1-2-showcase-1/WebHome/download%20-%202022-02-10T131102.033.png?rev=1.1||alt="regional bias vs goodness of fit"]]
107 +[[image:download - 2022-02-10T131102.033.png||alt="regional bias vs goodness of fit"]]
107 107  )))
108 108  
109 109